Environmental regulation, spatial spillover, and agricultural green total factor productivity: an analysis based on panel data from the Yangtze River economic belt

doi:10.16178/j.issn.0528-9017.20250531

Abstract

Abstract:

This study is based on the theory of spatial spillover effects and uses panel data from 11 provinces and municipalities in the Yangtze River economic belt from 2007 to 2023 to systematically investigate the intrinsic relationship and mechanisms between environmental regulation and agricultural green total factor productivity. The research employs the entropy method to measure the intensity of environmental regulation, utilizes the super-efficiency SBM-GML model to assess agricultural green total factor productivity, and applies a two-way fixed effects spatial Durbin model to analyze spatial spillover effects. The results indicate that environmental regulation in the Yangtze River economic belt not only has a significant positive promoting effect on agricultural green total factor productivity in the local region but also exhibits clear spatial spillover effects. Furthermore, its impact shows spatial heterogeneity and is significantly constrained by the level of regional economic development. Based on these findings, the Yangtze River economic belt should scientifically leverage the restraining and incentivizing effects of environmental regulation, foster new quality productive forces in agriculture by enhancing technological innovation, implement differentiated and dynamic environmental regulation policies tailored to local conditions, strengthen regional coordination, and promote cross-basin joint pollution prevention and control.

Key words: environmental regulation, agricultural green total factor productivity, spatial spillover effect, Yangtze River economic belt

CLC Number:

ZHANG Hang, KONG Lingcheng. Environmental regulation, spatial spillover, and agricultural green total factor productivity: an analysis based on panel data from the Yangtze River economic belt[J]. Journal of Zhejiang Agricultural Sciences, 2026, 67(1): 271-280.

Figures/Tables 8

References 36

[1]	魏下海, 余玲铮. 中国全要素生产率变动的再测算与适用性研究: 基于数据包络分析与随机前沿分析方法的比较[J]. 华中农业大学学报(社会科学版), 2011(3): 76-83.
	WEI X H, YU L Z. Reestimating total factor productivity growth of China and its applicability: a comparison between DEA and SFA[J]. Journal of Huazhong Agricultural University (Social Sciences Edition), 2011(3): 76-83.
[2]	吴传清, 宋子逸. 长江经济带农业绿色全要素生产率测度及影响因素研究[J]. 科技进步与对策, 2018, 35(17): 35-41.
	WU C Q, SONG Z Y. Study on the measurement and affecting factors of agricultural green total factor productivity in the Yangtze River economic belt[J]. Science & Technology Progress and Policy, 2018, 35(17): 35-41.
[3]	韩海彬, 赵丽芬. 环境约束下中国农业全要素生产率增长及收敛分析[J]. 中国人口·资源与环境, 2013, 23(3): 70-76.
	HAN H B, ZHAO L F. Growth and convergence of agricultural total factor productivity in China under environmental regulations[J]. China Population, Resources and Environment, 2013, 23(3): 70-76.
[4]	张焱. 数字经济、溢出效应与全要素生产率提升[J]. 贵州社会科学, 2021(3): 139-145.
	ZHANG Y. Digital economy, spillover effect and total factor productivity improvement[J]. Guizhou Social Sciences, 2021(3): 139-145.
[5]	杜江, 王锐, 王新华. 环境全要素生产率与农业增长: 基于DEA-GML指数与面板Tobit模型的两阶段分析[J]. 中国农村经济, 2016(3): 65-81.
	DU J, WANG R, WANG X H. Environmental total factor productivity and agricultural growth: a two-stage analysis based on DEA-GML index and panel Tobit model[J]. Chinese Rural Economy, 2016(3): 65-81.
[6]	袁芳, 张红丽, 陈文新. 西北地区绿色农业投资效率水平测度及空间差异[J]. 统计与决策, 2020, 36(24): 70-73.
	YUAN F, ZHANG H L, CHEN W X. Measurement and spatial difference of investment efficiency level of green agriculture in northwest China[J]. Statistics & Decision, 2020, 36(24): 70-73.
[7]	徐永慧, 尹朝静. 环境规制下中国农业绿色全要素生产率的测算[J]. 统计与决策, 2021, 37(18): 50-54.
	XU Y H, YIN C J. Measurement on green total factor productivity of China's agriculture under environmental regulation[J]. Statistics & Decision, 2021, 37(18): 50-54.
[8]	胡永浩, 张昆扬, 武拉平, 等. 环境规制对农业绿色全要素生产率的影响[J]. 生态经济, 2023, 39(12): 118-125.
	HU Y H, ZHANG K Y, WU L P, et al. Influence of environmental regulation on agricultural green total factor productivity[J]. Ecological Economy, 2023, 39(12): 118-125.
[9]	倪瑛, 陈柏云, 王忆雯. 金融发展、环境规制与绿色全要素生产率: 基于空间杜宾模型的实证分析[J]. 贵州财经大学学报, 2020(3): 12-21.
	NI Y, CHEN B Y, WANG Y W. Financial development, environmental regulation and green total factor productivity-an empirical analysis based on spatial Durbin model[J]. Journal of Guizhou University of Finance and Economics, 2020(3): 12-21.
[10]	胡雪萍, 乐冬. 环境规制促进了农业全要素生产率提升吗?[J]. 江汉论坛, 2022(11): 42-51.
	HU X P, LE D. Does environmental regulation promote agricultural total factor productivity?[J]. Jianghan Tribune, 2022(11): 42-51.
[11]	HU Y H, GUO X, ZHANG L, et al. Environmental regulation, innovation choices, and agricultural green total factor productivity under a multi-regulatory perspective[J]. Environmental Science and Pollution Research, 2024, 31(32): 45117-45137.
[12]	秦腾, 章恒全. 农业发展进程中的水环境约束效应及影响因素研究: 以长江流域为例[J]. 南京农业大学学报(社会科学版), 2017, 17(2): 134-142.
	QIN T, ZHANG H Q. Study on water environment constraint effect and its influencing factors in the process of agricultural development-a case study of the Yangtze River basin[J]. Journal of Nanjing Agricultural University (Social Sciences Edition), 2017, 17(2): 134-142.
[13]	尹礼汇, 吴传清. 环境规制与长江经济带污染密集型产业生态效率[J]. 中国软科学, 2021(8): 181-192.
	YIN L H, WU C Q. Environmental regulation and the ecological efficiency of pollution-intensive industries in the Yangtze River economic belt[J]. China Soft Science, 2021(8): 181-192.
[14]	YUAN B L, XIANG Q L. Environmental regulation, industrial innovation and green development of Chinese manufacturing: Based on an extended CDM model[J]. Journal of Cleaner Production, 2018, 176: 895-908.
[15]	郭家兵. 环境规制对农业绿色全要素生产率的影响研究: 以浙江省为例[J]. 生产力研究, 2023(5): 89-93.
	GUO J B. Study on the impact of environmental regulation on agricultural green total factor productivity: taking Zhejiang Province as an example[J]. Productivity Research, 2023(5): 89-93.
[16]	马国群, 谭砚文. 环境规制对农业绿色全要素生产率的影响研究: 基于面板门槛模型的分析[J]. 农业技术经济, 2021(5): 77-92.
	MA G Q, TAN Y W. Impact of environmental regulation on agricultural green total factor productivity: analysis based on the panel threshold model[J]. Journal of Agrotechnical Economics, 2021(5): 77-92.
[17]	马海良, 顾莹莹, 黄德春, 等. 环境规制、数字赋能对产业结构升级的影响及机理[J]. 中国人口·资源与环境, 2024, 34(3): 124-136.
	MA H L, GU Y Y, HUANG D C, et al. Impact and mechanisms of environmental regulation and digital empowerment on industrial structure upgrading[J]. China Population Resources and Environment, 2024, 34(3): 124-136.
[18]	朱金鹤, 王雅莉. 创新补偿抑或遵循成本? 污染光环抑或污染天堂?: 绿色全要素生产率视角下双假说的门槛效应与空间溢出效应检验[J]. 科技进步与对策, 2018, 35(20): 46-54.
	ZHU J H, WANG Y L. “Innovation compensation”or “following costs”? “pollution paradise” or “pollution halo”?: the threshold effect of double hypothesis and the test of spatial spillover effect from the perspective of green total factor productivity[J]. Science & Technology Progress and Policy, 2018, 35(20): 46-54.
[19]	夏建红, 刘松, 丁晨峰, 等. 环境规制与绿色全要素生产率: 促进还是抑制?[J]. 经济问题, 2024(4): 60-67.
	XIA J H, LIU S, DING C F, et al. Environmental regulation and green total factor productivity: promoting or suppressing?[J]. On Economic Problems, 2024(4): 60-67.
[20]	孙杰刚, 杨军. 地方政府竞争与绿色全要素生产率[J]. 经济问题, 2023(11): 114-121.
	SUN J G, YANG J. Local government competition and green total factor productivity[J]. On Economic Problems, 2023(11): 114-121.
[21]	袁嘉琪, 卜伟, 唐雨妮. 环境规制、要素配置对工业绿色全要素生产率的影响: 产出补偿还是创新补偿[J]. 管理评论, 2023(10): 45-62.
	YUAN J Q, BU W, TANG Y N. The influence of environmental regulation and factor allocation on industrial green TFP: output compensation or innovation compensation[J]. Management Review, 2023(10): 45-62.
[22]	冯斐, 冯学钢, 侯经川, 等. 经济增长、区域环境污染与环境规制有效性: 基于京津冀地区的实证分析[J]. 资源科学, 2020, 42(12): 2341-2353.
	FENG F, FENG X G, HOU J C, et al. Effectiveness of regional environmental regulation, economic growth and environmental pollution: an emprical study of the Beijing-Tianjin-Hebei region[J]. Resources Science, 2020, 42(12): 2341-2353.
[23]	李波, 张俊飚, 李海鹏. 中国农业碳排放时空特征及影响因素分解[J]. 中国人口·资源与环境, 2011, 21(8): 80-86.
	LI B, ZHANG J B, LI H P. Research on spatial-temporal characteristics and affecting factors decomposition of agricultural carbon emission in China[J]. China Population Resources and Environment, 2011, 21(8): 80-86.
[24]	饶静, 许翔宇, 纪晓婷. 我国农业面源污染现状、发生机制和对策研究[J]. 农业经济问题, 2011, 32(8): 81-87.
	RAO J, XU X Y, JI X T. Study on the present situation, occurrence mechanism and countermeasures of agricultural non-point source pollution in China[J]. Issues in Agricultural Economy, 2011, 32(8): 81-87.
[25]	周风, 文春晖. 提升还是抑制: 环境规制如何影响农业绿色全要素生产率[J/OL]. 中国农业资源与区划, 2024: 1-16. ( 2024-12-17)[2025-07-23]. https://kns.cnki.net/KCMS/detail/detail.aspx?filename=ZGNZ2024121100A&dbname=CJFD&dbcode=CJFQ.
	ZHOU F, WEN C H. Promotion or inhibition: how does environmental regulation affect agricultural green total factor productivity[J/OL]. Chinese Journal of Agricultural Resources and Regional Planning, 2024: 1-16. ( 2024-12-17)[2025-07-23]. https://kns.cnki.net/KCMS/detail/detail.aspx?filename=ZGNZ2024121100A&dbname=CJFD&dbcode=CJFQ.
[26]	刘荣增, 何春. 环境规制对城镇居民收入不平等的门槛效应研究[J]. 中国软科学, 2021(8): 41-52.
	LIU R Z, HE C. Study on the threshold effect of environmental regulation on income inequality of urban residents[J]. China Soft Science, 2021(8): 41-52.
[27]	陈庭强, 张情, 刘梦, 等. 环境规制下绿色金融驱动产业绿色发展的实证研究[J]. 南京工业大学学报(社会科学版), 2023, 22(3): 76-94, 114.
	CHEN T Q, ZHANG Q, LIU M, et al. An empirical study on the green development of industry driven by green finance under environmental regulation[J]. Journal of Nanjing Tech University (Social Science Edition), 2023, 22(3): 76-94, 114.
[28]	王玉爽. 环境规制对绿色全要素生产率的影响: 基于环境分权和空间溢出视角[J]. 中国流通经济, 2023, 37(9): 63-79.
	WANG Y S. Research on the impact of environmental regulation on green total factor productivity: based on the perspective of environmental decentralization and spatial spillover[J]. China Business and Market, 2023, 37(9): 63-79.
[29]	肖远飞, 吴允. 财政分权、环境规制与绿色全要素生产率: 基于动态空间杜宾模型的实证分析[J]. 华东经济管理, 2019, 33(11): 15-23.
	XIAO Y F, WU Y. Fiscal decentralization, environmental regulation and green total factor productivity: an empirical analysis based on dynamic spatial Durbin model[J]. East China Economic Management, 2019, 33(11): 15-23.
[30]	李小平, 余东升, 余娟娟. 异质性环境规制对碳生产率的空间溢出效应: 基于空间杜宾模型[J]. 中国软科学, 2020(4): 82-96.
	LI X P, YU D S, YU J J. Spatial spillover effect of heterogeneous environmental regulations on carbon productivity: spatial Durbin model[J]. China Soft Science, 2020(4): 82-96.
[31]	游达明, 欧阳乐茜. 环境规制对工业企业绿色创新效率的影响: 基于空间杜宾模型的实证分析[J]. 改革, 2020(5): 122-138.
	YOU D M, OUYANG L Q. The impact of environmental regulation on the green innovation efficiency of industrial enterprises: an empirical analysis based on the spatial Durbin model[J]. Reform, 2020(5): 122-138.
[32]	李宇星, 刘寒波. 财政纵向失衡、地方政府行为与绿色全要素生产率[J]. 科学决策, 2024(10): 201-214.
	LI Y X, LIU H B. Fiscal vertical imbalances, local government behavior and green total factor productivity[J]. Scientific Decision Making, 2024(10): 201-214.
[33]	黄倩, 李江城, 熊德平. 金融风险视角下金融杠杆对经济增长的影响研究[J]. 改革, 2021(4): 78-94.
	HUANG Q, LI J C, XIONG D P. The Impact of Financial Leverage on Economic Growth from the Perspective of Financial Risk[J]. Reform, 2021(4): 78-94.
[34]	惠炜, 赵国庆. 环境规制与污染避难所效应: 基于中国省际数据的面板门槛回归分析[J]. 经济理论与经济管理, 2017(2): 23-33.
	HUI W, ZHAO G Q. Environmental regulation and pollution haven: an Empirical Analysis Based on Panel Threshold Regression of Chinese Provincial Data[J]. Economic Theory and Business Management, 2017(2): 23-33.
[35]	何寿奎, 辜迪. 新基建、产业升级与绿色全要素生产率空间效应研究[J]. 生态经济, 2025, 41(3): 64-74.
	HE S K, GU D. Research on spatial effects of new infrastructure, industrial upgrading and green total factor productivity[J]. Ecological Economy, 2025, 41(3): 64-74.
[36]	杜克锐, 欧阳晓灵, 郑泳薇. 环境规制是否促进我国城市的绿色经济增长?[J]. 统计研究, 2023, 40(12): 39-49.
	DU K R, OUYANG X L, ZHENG Y W. Does environmental regulation promote green economic growth of Chinese Cities?[J]. Statistical Research, 2023, 40(12): 39-49.

变量	观测值	平均值	标准差	最小值	最大值
A	187	1.105	0.112	0.798	1.712
E	187	-0.464	0.161	-0.924	-0.190
L	187	2.276	0.131	1.823	2.538
S	187	1.192	0.416	0.619	3.058
O	187	9.838	0.341	6.772	12.200
N	187	0.298	0.333	0.027	1.670

变量	观测值	平均值	标准差	最小值	最大值
A	187	1.105	0.112	0.798	1.712
E	187	-0.464	0.161	-0.924	-0.190
L	187	2.276	0.131	1.823	2.538
S	187	1.192	0.416	0.619	3.058
O	187	9.838	0.341	6.772	12.200
N	187	0.298	0.333	0.027	1.670

年份	环境规制		农业全要素生产率
年份	Moran's I指数	p值	Moran's I指数	p值
2010	0.156	0.110	0.378^***	<0.001
2013	0.182^*	0.071	0.527^***	<0.001
2014	0.168^*	0.090	0.522^***	<0.001
2015	0.188^*	0.064	0.401^***	<0.001
2017	0.188^*	0.064	0.396^***	<0.001
2019	0.165^*	0.096	0.354^**	0.001
2022	0.162^*	0.100	0.148	0.121
2023	0.168^*	0.090	0.146	0.117

年份	环境规制		农业全要素生产率
年份	Moran's I指数	p值	Moran's I指数	p值
2010	0.156	0.110	0.378^***	<0.001
2013	0.182^*	0.071	0.527^***	<0.001
2014	0.168^*	0.090	0.522^***	<0.001
2015	0.188^*	0.064	0.401^***	<0.001
2017	0.188^*	0.064	0.396^***	<0.001
2019	0.165^*	0.096	0.354^**	0.001
2022	0.162^*	0.100	0.148	0.121
2023	0.168^*	0.090	0.146	0.117

检验方法	原假设	统计值	p值	结果
LR检验	SDM退化为SAR	17.161	0.004	拒绝原假设
	SDM退化为SEM	9.771	0.082	拒绝原假设
Wald检验	SDM退化为SAR	18.150	0.003	拒绝原假设
	SDM退化为SEM	14.971	0.020	拒绝原假设